计算机集成制造系统 ›› 2017, Vol. 23 ›› Issue (第10): 2229-2240.DOI: 10.13196/j.cims.2017.10.017

• 产品创新开发技术 • 上一篇    下一篇

逆向供应链服务组合与优化

曹建华1,夏绪辉1,王蕾1,2+,周文斌1,刘翔1   

  1. 1.武汉科技大学冶金装备及其控制教育部重点实验室
    2.武汉科技大学冶金矿产资源高效利用与造块湖北省重点实验室
  • 出版日期:2017-10-31 发布日期:2017-10-31
  • 基金资助:
    国家自然科学基金资助项目(71471143);武汉科技大学冶金矿产资源高效利用与造块湖北省重点实验室资助项目(2016zy013);国家级大学生创新创业训练计划资助项目(201510488105)。

Composition and optimization of reverse supply chain services

  • Online:2017-10-31 Published:2017-10-31
  • Supported by:
    Project supported by the National Natural Science Foundation,China(No.71471143),the Hubei Provincial Key Laboratory for Efficient Utilization and Agglomerationof Metallurgic Mineral Resources,China(No.2016zy013),and the National College Students Innovative & Entrepreneual Training Program,China(No.201510488105).

摘要: 针对逆向供应链服务组合中协作与竞争并存的组合模式,提出一种逆向供应链服务活动组合、服务资源优化的两阶段服务组合方法。通过基于语义本体的逆向供应链服务形式化描述方式,提出一种“正向组合—逆向缩减”的逆向供应链服务活动组合方法;利用带约束的多目标双种群遗传优化算法,以服务时间、服务成本和服务质量等逆向供应链服务质量指标为优化目标,针对服务活动方案对应的服务资源进行优化组合选择,得到全局最优的服务资源组合方案,为服务需求者提供决策支持;以废钢逆向供应链服务组合为例对该逆向供应链服务组合方法进行了验证,并结合带精英策略的非支配排序遗传算法对优化算法的收敛性与多样性进行有效性分析。

关键词: 逆向供应链, 服务组合, 双种群遗传算法, 多目标优化

Abstract: Aiming at the coexistence problem of cooperation and competition in reverse supply chain service combination,a two-stage method for service composition was proposed.Through the formal description method based on semantic ontology,a combination method of reverse supply chain service activities was presented.To obtain the global optimum excellent service resource combination regimen through the program of service activities,a multi-objective dual population genetic algorithm with constraints was put forward for the optimization objectives of service time,service costs and service quality,which were QoS indicators of reverse supply chain.A case on the demand of steel scrap was taken as an example to validate the effectiveness of the proposed method,and the convergence and diversity of the proposed genetic algorithm were analyzed by comparison with elitist Non-dominated Sorting Genetic Algorithm (NSGA-Ⅱ).

Key words: reverse supply chain services, services composition, dual population genetic algorithm, multi-objective optimization

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